System and method of detecting whether a source of a packet flow transmits packets which bypass an operating system stack

ABSTRACT

A method includes capturing first data associated with a first packet flow originating from a first host using a first capture agent deployed at the first host to yield first flow data, capturing second data associated with a second packet flow originating from the first host from a second capture agent deployed on a second host to yield second flow data and comparing the first flow data and the second flow data to yield a difference. When the difference is above a threshold value, the method includes determining that the second packet flow was transmitted by a component that bypassed an operating stack of the first host or a packet capture agent at the device to yield a determination, detecting that hidden network traffic exists, and predicting a malware issue with the first host based on the determination.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application No.62/171,899, entitled “SYSTEM FOR MONITORING AND MANAGING DATACENTERS,”filed on Jun. 5, 2015, which is incorporated herein by reference in itsentirety.

TECHNICAL FIELD

The present disclosure pertains to network analytics, and morespecifically a system for detecting malicious activity within a networkby analyzing data captured by sensors deployed at multiple layersthroughout a network.

BACKGROUND

Network architectures for observing and capturing information aboutnetwork traffic in a datacenter are described herein. Network trafficcoming out of a compute environment (whether from a container, VM,hardware switch, hypervisor or physical server) is captured by entitiescalled sensors or capture agents that can be deployed in or insidedifferent environments. Sensors export data or metadata of the observednetwork activity to collection agents called “Collectors.” Collectorscan be a group of processes running on a single machine or a cluster ofmachines. For the sake of simplicity, collectors can be treated as onelogical entity and referred to as one collector. In actual deployment onthe datacenter scale, there will be more than just one collector, eachresponsible for handling export data from a group of sensors. Collectorsare capable of doing preprocessing and analysis of the data collectedfrom sensors. The collector is capable of sending the processed orunprocessed data to a cluster of processes responsible for analysis ofnetwork data. The entities which receive the data from the collector canbe a cluster of processes, and this logical group can be considered orreferred to as a “pipeline.” Note that sensors and collectors are notlimited to observing and processing just network data, but can alsocapture other system information like currently active processes, activefile handles, socket handles, status of I/O devices, memory, etc.

A network will often experience different amounts of packet loss atdifferent points within the path of a flow. It is important to identifythe amount of packet loss at each point to fine tune and improve thenetwork. Current solutions implement a request/reply model when tryingto identify packet loss at different points. In this approach, a systemwill send a request at each point and will identify packet loss if areply is not received. However, this model cannot be implemented in alive environment. Moreover, this model is not as efficient or accurateas it can lead to additional network traffic and be subject to errors.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary embodiments of the disclosure and are nottherefore to be considered to be limiting of its scope, the principlesherein are described and explained with additional specificity anddetail through the use of the accompanying drawings in which:

FIG. 1 illustrates a diagram of an example network environment;

FIG. 2A illustrates a schematic diagram of an example capturing agentdeployment in a virtualized environment;

FIG. 2B illustrates a schematic diagram of an example capturing agentdeployment in an example network device;

FIG. 2C illustrates a schematic diagram of an example reporting systemin an example capturing agent topology;

FIG. 3 illustrates a schematic diagram of an example configuration forcollecting capturing agent reports;

FIG. 4 illustrates an example method embodiment;

FIG. 5 illustrates a listing of example fields on a capturing agentreport;

FIG. 6 illustrates an example network device; and

FIGS. 7A and 7B illustrate example system embodiments.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Various embodiments of the disclosure are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the disclosure.

Overview

It is advantageous to identify the amount of packet loss at each pointin a network and to fine tune and improve the network. Prior artsolutions noted above implement a request/reply model when trying toidentify packet loss at different points. However, unlike the conceptsdisclosed herein, the prior model cannot be implemented in a liveenvironment. Moreover, the model is not as efficient or accurate as theconcepts disclosed herein. The present disclosure provides systems thatdetect malicious activity by capturing data associated with a packetflow from a location within the device or host generating the packetflow as well as capturing second data associated with the packet flowfrom a location outside of the device or host. The sets of data arecompared to determine whether the packet flow includes hidden networktraffic, at which point the system can take corrective action and adjustto limit the harm caused by the threat.

Additional features and advantages of the disclosure will be set forthin the description which follows, and in part will be obvious from thedescription, or can be learned by practice of the herein disclosedprinciples. The features and advantages of the disclosure can berealized and obtained by means of the instruments and combinationsparticularly pointed out in the appended claims. These and otherfeatures of the disclosure will become more fully apparent from thefollowing description and appended claims, or can be learned by thepractice of the principles set forth herein.

Disclosed are systems, methods, and computer-readable storage media forcapturing first data associated with a first packet flow originatingfrom a computing device or host using a first capture agent deployed atthe computing device or host to yield first flow data, capturing seconddata associated with a second packet flow originating from the computingdevice or host from a second capture agent deployed outside of thecomputing device or host to yield second flow data, and comparing thefirst flow data and the second flow data to yield a difference. When thedifference is above a threshold value, the method includes determiningthat the second packet flow was transmitted by a component that bypassedone of an operating stack of the computing device or host and a packetcapture agent on the computing device or host.

The first data and the second data can include metadata associatedrespectively with the first packet flow and the second packet flow orfirst packet content of the first packet flow and second packet contentof the second packet flow. The data can also include network data. Acollector can receive the first flow data and the second flow data andperform the step of comparing the first flow data and the second flowdata. When the difference is above a threshold value, the step ofdetermining that the second packet flow was transmitted by a componentthat bypassed one of the operating stack of the computing device and thepacket capture agent of the computing device further includesdetermining that hidden network traffic exists.

When the hidden network traffic exists, the method further includesperforming a correcting action including one or more of: isolating avirtual machine, isolating a container, limiting packets to and from thecomputing device, requiring all packets to and from the computing deviceor host to flow through an operating stack of the computing device orhost, isolating the computing device, shutting down the computing deviceor host, blacklisting the hidden network traffic and/or any entitiesassociated with the hidden network traffic such as a sender or source,tagging or flagging the hidden network traffic, adjusting thegranularity of reported or captured data associated with the hiddennetwork traffic or an associated entity, adjusting a network or securitypolicy such as a routing or firewall policy, and notifying anadministrator.

The method can also include identifying a computing environment thatgenerated the first packet flow and the second packet flow. Based on thedetermination, the method also can include determining that hiddennetwork traffic exists and/or thereafter taking a corrective action or alimiting action to reduce the negative effect of the threat. With theinformation identified from the collector, the system can also predict apresence of a malicious entity in the computing device based on thehidden network traffic and/or other data.

Description

The disclosed technology addresses the need in the art for identifyingmalicious processes within a network. A description of an examplenetwork environment, as illustrated in FIG. 1, is first disclosedherein. A discussion of capturing agents will then follow. Thedisclosure continues with a discussion of the specific process foridentifying a lineage for a process or processes and then determiningthrough the study of the lineage whether a process is malicious. Thediscussion then concludes with a description of example systems anddevices. These variations shall be described herein as the variousembodiments are set forth. The disclosure now turns to FIG. 1.

FIG. 1 illustrates a diagram of example network environment 100. Fabric112 can represent the underlay (i.e., physical network) of networkenvironment 100. Fabric 112 can include spine routers 1-N (102 _(A-N))(collectively “102”) and leaf routers 1-N (104 _(A-N)) (collectively“104”). Leaf routers 104 can reside at the edge of fabric 112, and canthus represent the physical network edges. Leaf routers 104 can be, forexample, top-of-rack (“ToR”) switches, aggregation switches, gateways,ingress and/or egress switches, provider edge devices, and/or any othertype of routing or switching device.

Leaf routers 104 can be responsible for routing and/or bridging tenantor endpoint packets and applying network policies. Spine routers 102 canperform switching and routing within fabric 112. Thus, networkconnectivity in fabric 112 can flow from spine routers 102 to leafrouters 104, and vice versa.

Leaf routers 104 can provide servers 1-4 (106 _(A-D)) (collectively“106”), hypervisors 1-3 (108 _(A)-108 _(C)) (collectively “108”),virtual machines (VMs) 1-4 (110 _(A)-110 _(D)) (collectively “110”),collectors 118, engines 120, and the Layer 2 (L2) network access tofabric 112. For example, leaf routers 104 can encapsulate anddecapsulate packets to and from servers 106 in order to enablecommunications throughout environment 100. Leaf routers 104 can alsoconnect other network-capable device(s) or network(s), such as afirewall, a database, a server, etc., to the fabric; 112. Leaf routers104 can also provide any other servers, resources, endpoints, externalnetworks, VMs, services, tenants, or workloads with access to fabric112.

VMs 110 can be virtual machines hosted by hypervisors 108 running onservers 106. VMs 110 can include workloads running on a guest operatingsystem on a respective server. Hypervisors 108 can provide a layer ofsoftware, firmware, and/or hardware that creates and runs the VMs 110.Hypervisors 108 can allow VMs 110 to share hardware resources on servers106, and the hardware resources on servers 106 to appear as multiple,separate hardware platforms. Moreover, hypervisors 108 and servers 106can host one or more VMs 110. For example, server 106 _(A) andhypervisor 108 _(A) can host VMs 110 _(A-B).

In some cases, VMs 110 and/or hypervisors 108 can be migrated to otherservers 106. For example, VM 110 _(A) can be migrated to server 106 _(C)and hypervisor 108 _(B). Servers 106 can similarly be migrated to otherlocations in network environment 100. For example, a server connected toa specific leaf router can be changed to connect to a different oradditional leaf router. In some cases, some or all of servers 106,hypervisors 108, and/or VMs 110 can represent tenant space. Tenant spacecan include workloads, services, applications, devices, and/or resourcesthat are associated with one or more clients or subscribers.Accordingly, traffic in network environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants.

Any of leaf routers 104, servers 106, hypervisors 108, and VMs 110 caninclude capturing agent 116 (also referred to as a “sensor” or a“capturing agent”) configured to capture network data, and report anyportion of the captured data to collector 118. Capturing agents 116 canbe processes, agents, modules, drivers, or components deployed on arespective system or system layer (e.g., a server, VM, virtualcontainer, hypervisor, leaf router, etc.), configured to capture networkdata for the respective system (e.g., data received or transmitted bythe respective system), and report some or all of the captured data andstatistics to collector 118.

For example, a VM capturing agent can run as a process, kernel module,software element, or kernel driver on the guest operating systeminstalled in a VM and configured to capture and report data (e.g.,network and/or system data) processed (e.g., sent, received, generated,etc.) by the VM.

A hypervisor capturing agent can run as a process, kernel module,software element, or kernel driver on the host operating systeminstalled at the hypervisor layer and configured to capture and reportdata (e.g., network and/or system data) processed (e.g., sent, received,generated, etc.) by the hypervisor.

A container capturing agent can run as a process, kernel module,software element, or kernel driver on the operating system of a device,such as a switch or server, which can be configured to capture andreport data processed by the container.

A server capturing agent can run as a process, kernel module, softwareelement, or kernel driver on the host operating system of a server andconfigured to capture and report data (e.g., network and/or system data)processed (e.g., sent, received, generated, etc.) by the server.

A network device capturing agent can run as a process, software element,or component in a network device, such as leaf routers 104, andconfigured to capture and report data (e.g., network and/or system data)processed (e.g., sent, received, generated, etc.) by the network device.

Capturing agents 116 can be configured to report observed data,statistics, and/or metadata about one or more packets, flows,communications, processes, events, and/or activities to collector 118.For example, capturing agents 116 can capture network data andstatistics processed (e.g., sent, received, generated, dropped,forwarded, etc.) by the system or host (e.g., server, hypervisor, VM,container, switch, etc.) of the capturing agents 116 (e.g., where thecapturing agents 116 are deployed). The capturing agents 116 can alsoreport the network data and statistics to one or more devices, such ascollectors 118 and/or engines 120. For example, the capturing agents 116can report an amount of traffic processed by their host, a frequency ofthe traffic processed by their host, a type of traffic processed (e.g.,sent, received, generated, etc.) by their host, a source or destinationof the traffic processed by their host, a pattern in the traffic, anamount of traffic dropped or blocked by their host, types of requests ordata in the traffic received, discrepancies in traffic (e.g., spoofedaddresses, invalid addresses, hidden sender, etc.), protocols used incommunications, type or characteristics of responses to traffic by thehosts of the capturing agents 116, what processes have triggeredspecific packets, etc.

Capturing agents 116 can also capture and report information about thesystem or host of the capturing agents 116 (e.g., type of host, type ofenvironment, status of host, conditions of the host, etc.). Suchinformation can include, for example, data or metadata of active orpreviously active processes of the system, operating system useridentifiers, kernel modules loaded or used, network softwarecharacteristics (e.g., software switch, virtual network card, etc.),metadata of files on the system, system alerts, number and/or identityof applications at the host, domain information, networking information(e.g., address, topology, settings, connectivity, etc.), sessioninformation (e.g., session identifier), faults or errors, memory or CPUusage, threads, filename and/or path, services, security information orsettings, and so forth.

Capturing agents 116 may also analyze the processes running on therespective VMs, hypervisors, servers, or network devices to determinespecifically which process is responsible for a particular flow ofnetwork traffic. Similarly, capturing agents 116 may determine whichoperating system user (e.g., root, system, John Doe, Admin, etc.) isresponsible for a given flow. Reported data from capturing agents 116can provide details or statistics particular to one or more tenants orcustomers. For example, reported data from a subset of capturing agents116 deployed throughout devices or elements in a tenant space canprovide information about the performance, use, quality, events,processes, security status, characteristics, statistics, patterns,conditions, configurations, topology, and/or any other information forthe particular tenant space.

Collectors 118 can be one or more devices, modules, workloads, VMs,containers, and/or processes capable of receiving data from capturingagents 116. Collectors 118 can thus collect reports and data fromcapturing agents 116. Collectors 118 can be deployed anywhere in networkenvironment 100 and/or even on remote networks capable of communicatingwith network environment 100. For example, one or more collectors can bedeployed within fabric 112, on the L2 network, or on one or more of theservers 106, VMs 110, hypervisors. Collectors 118 can be hosted on aserver or a cluster of servers, for example. In some cases, collectors118 can be implemented in one or more servers in a distributed fashion.

As previously noted, collectors 118 can include one or more collectors.Moreover, a collector can be configured to receive reported data fromall capturing agents 116 or a subset of capturing agents 116. Forexample, a collector can be assigned to a subset of capturing agents 116so the data received by that specific collector is limited to data fromthe subset of capturing agents 116. Collectors 118 can be configured toaggregate data from all capturing agents 116 and/or a subset ofcapturing agents 116. Further, collectors 118 can be configured toanalyze some or all of the data reported by capturing agents 116.

Environment 100 can include one or more analytics engines 120 configuredto analyze the data reported to collectors 118. For example, engines 120can be configured to receive collected data from collectors 118,aggregate the data, analyze the data (individually and/or aggregated),generate reports, identify conditions, compute statistics, visualizereported data, troubleshoot conditions, visualize the network and/orportions of the network (e.g., a tenant space), generate alerts,identify patterns, calculate misconfigurations, identify errors,generate suggestions, generate testing, detect compromised elements(e.g., capturing agents 116, devices, servers, switches, etc.), and/orperform any other analytics functions.

Engines 120 can include one or more modules or software programs forperforming such analytics. Further, engines 120 can reside on one ormore servers, devices, VMs, nodes, etc. For example, engines 120 can beseparate VMs or servers, an individual VM or server, or a cluster ofservers or applications. Engines 120 can reside within the fabric 112,within the L2 network, outside of the environment 100 WAN 114), in oneor more segments or networks coupled with the fabric 112 (e.g., overlaynetwork coupled with the fabric 112), etc. Engines 120 can be coupledwith the fabric 112 via the leaf switches 104, for example.

While collectors 118 and engines 120 are shown as separate entities,this is simply a non-limiting example for illustration purposes, asother configurations are also contemplated herein. For example, any ofcollectors 118 and engines 120 can be part of a same or separate entity.Moreover, any of the collector, aggregation, and analytics functions canbe implemented by one entity (e.g., a collector 118 or engine 120) orseparately implemented by multiple entities (e.g., engines 120 and/orcollectors 118).

Each of the capturing agents 116 can use a respective address (e.g.,internet protocol (IP) address, port number, etc.) of their host to sendinformation to collectors 118 and/or any other destination. Collectors118 may also be associated with their respective addresses such as IPaddresses. Moreover, capturing agents 116 can periodically sendinformation about flows they observe to collectors 118. Capturing agents116 can be configured to report each and every flow they observe or asubset of flows they observe. For example, capturing agents 116 canreport every flow always, every flow within a period of time, every flowat one or more intervals, or a subset of flows during a period of timeor at one or more intervals.

Capturing agents 116 can report a list of flows that were active duringa period of time (e.g., between the current time and the time of thelast report). The consecutive periods of time of observance can berepresented as pre-defined or adjustable time series. The series can beadjusted to a specific level of granularity. Thus, the time periods canbe adjusted to control the level of details in statistics and can becustomized based on specific requirements or conditions, such assecurity, scalability, bandwidth, storage, etc. The time seriesinformation can also be implemented to focus on more important, flows orcomponents (e.g., VMs) by varying the time intervals. The communicationchannel between a capturing agent and collector 118 can also create aflow in every reporting interval. Thus, the information transmitted orreported by capturing agents 116 can also include information about theflow created by the communication channel.

When referring to a capturing agent's host herein, the host can refer tothe physical device or component hosting the capturing agent (e.g.,server, networking device, ASIC, etc.), the virtualized environmenthosting the capturing agent (e.g., hypervisor, virtual machine, etc.),the operating system hosting the capturing agent (e.g., guest operatingsystem, host operating system, etc.), and/or system layer hosting thecapturing agent (e.g., hardware layer, operating system layer,hypervisor layer, virtual machine layer, etc.).

FIG. 2A illustrates a schematic diagram of an example capturing agentdeployment 200 in a server 106 _(A). Server 106 _(A) can execute andhost one or more VMs 110 _(A-N) (collectively “110”). VMs 110 can beconfigured to run workloads (e.g., applications, services, processes,functions, etc.) based on hardware resources 210 on server 106 _(A). VMs110 can run on guest operating systems 204 _(A-N) (collectively “204”)on a virtual operating platform provided by hypervisor 108 _(A). Each VM110 can run a respective guest operating system 204 which can be thesame or different as other guest operating systems 204 associated withother VMs 110 on server 106 _(A). Each of guest operating systems 204can execute one or more processes, which may in turn be programs,applications, modules, drivers, services, widgets, etc. Moreover, eachVM 110 can have one or more network addresses, such as an internetprotocol (IP) address. VMs 110 can thus communicate with hypervisor 108_(A), server 106 _(A), and/or any remote devices or networks using theone or more network addresses.

Hypervisor 108 _(A) (otherwise known as a virtual machine manager ormonitor) can be a layer of software, firmware, and/or hardware thatcreates and runs VMs 110. Guest operating systems 204 running on VMs 110can share virtualized hardware resources created by hypervisor 108 _(A).The virtualized hardware resources can provide the illusion of separatehardware components. Moreover, the virtualized hardware resources canperform as physical hardware components (e.g., memory, storage,processor, network interface, peripherals, etc.), and can be driven byhardware resources 210 on server 106 _(A). Hypervisor 108 _(A) can haveone or more network addresses, such as an internet protocol (IP)address, to communicate with other devices, components, or networks. Forexample, hypervisor 108 _(A) can have a dedicated IP address which itcan use to communicate with VMs 110, server 106 _(A), and/or any remotedevices or networks.

Hypervisor 108 _(A) can be assigned a network address, such as an IP,with a global scope. For example, hypervisor 108 _(A) can have an IPthat can be reached or seen by VMs 110 _(A-N) as well any other devicesin the network environment 100 illustrated in FIG. 1. On the other hand,VMs 110 can have a network address, such as an IP, with a local scope.For example, VM 110 _(A) can have an IP that is within a local networksegment where VM 110 _(A) resides and/or which may not be directlyreadied or seen from other network segments in the network environment100.

Hardware resources 210 of server 106 _(A) can provide the underlyingphysical hardware that drive operations and functionalities provided byserver 106 _(A), hypervisor 108 _(A), and VMs 110. Hardware resources210 can include, for example, one or more memory resources, one or morestorage resources, one or more communication interfaces, one or moreprocessors, one or more circuit boards, one or more buses, one or moreextension cards, one or more power supplies, one or more antennas, oneor more peripheral components, etc.

Server 106 _(A) can also include one or more host operating systems (notshown). The number of host operating systems can vary by configuration.For example, some configurations can include a dual boot configurationthat allows server 106 _(A) to boot into one of multiple host operatingsystems. In other configurations, server 106 _(A) may run a single hostoperating system. Host operating systems can run on hardware resources210. In some cases, hypervisor 108 _(A) can run on, or utilize, a hostoperating system on server 106 _(A). Each of the host operating systemscan execute one or inure processes, which may be programs, applications,modules, drivers, services, widgets, etc.

Server 106 _(A) can also have one or more network addresses, such as anIP address, to communicate with other devices, components, or networks.For example, server 106 _(A) can have an IP address assigned to acommunications interface from hardware resources 210, which it can useto communicate with VMs 110, hypervisor 108 _(A), leaf router 104 _(A)in FIG. 1, collectors 118 in FIG. 1, and/or any remote devices ornetworks.

VM capturing agents 202 _(A-N) (collectively “202”) can be deployed onone or more of VMs 110. VM capturing agents 202 can be data and packetinspection agents or sensors deployed on VMs 110 to capture packets,flows, processes, events, traffic, and/or any data flowing into, out of,or through VMs 110. VM capturing agents 202 can be configured to exportor report any data collected or captured by the capturing agents 202 toa remote entity, such as collectors 118, for example. VM capturingagents 202 can communicate or report such data using a network addressof the respective VMs 110 (e.g., VM IP address).

VM capturing agents 202 can capture and report any traffic (e.g.,packets, flows, etc.) sent, received, generated, and/or processed by VMs110. For example, capturing agents 202 can report every packet or flowof communication sent and received by VMs 110. Such communicationchannel between capturing agents 202 and collectors 108 creates a flowin every monitoring period or interval and the flow generated bycapturing agents 202 may be denoted as a control flow. Moreover, anycommunication sent or received by VMs 110, including data reported fromcapturing agents 202, can create a network flow. VM capturing agents 202can report such flows in the form of a control flow to a remote device,such as collectors 118 illustrated in FIG. 1.

VM capturing agents 202 can report each flow separately or aggregatedwith other flows. When reporting a flow via a control flow, VM capturingagents 202 can include a capturing agent identifier that identifiescapturing agents 202 as reporting the associated flow. VM capturingagents 202 can also include in the control flow a flow identifier, an IPaddress, a timestamp, metadata, a process ID, an OS username associatedwith the process ID, a host or environment descriptor (e.g., type ofsoftware bridge or virtual network card, type of host such as ahypervisor VM, etc.), and any other information, as further describedbelow. In addition, capturing agents 202 can append the process and userinformation (i.e., which process and/or user is associated with aparticular flow) to the control flow. The additional information asidentified above can be applied to the control flow as labels.Alternatively, the additional information can be included as part of aheader, a trailer, or a payload.

VM capturing agents 202 can also report multiple flows as a set offlows. When reporting a set of flows, VM capturing agents 202 caninclude a flow identifier for the set of flows and/or a flow identifierfor each flow in the set of flows. VM capturing agents 202 can alsoinclude one or more timestamps and other information as previouslyexplained.

VM capturing agents 202 can run as a process, kernel module, or kerneldriver on guest operating systems 204 of VMs 110. VM capturing agents202 can thus monitor any traffic sent, received, or processed by VMs110, any processes running on guest operating systems 204, any users anduser activities on guest operating system 204, any workloads on VMs 110,etc.

Hypervisor capturing agent 206 can be deployed on hypervisor 108 _(A).Hypervisor capturing agent 206 can be a data inspection agent or sensordeployed on hypervisor 108 _(A) to capture traffic (e.g., packets,flows, etc.) and/or data flowing through hypervisor 108 _(A). Hypervisorcapturing agent 206 can be configured to export or report any datacollected or captured by hypervisor capturing agent 206 to a remoteentity, such as collectors 118, for example. Hypervisor capturing agent206 can communicate or report such data using a network address ofhypervisor 108 _(A), such as an IP address of hypervisor 108 _(A).

Because hypervisor 108 _(A) can see traffic and data originating fromVMs 110, hypervisor capturing agent 206 can also capture and report anydata (e.g., traffic data) associated with VMs 110. For example,hypervisor capturing agent 206 can report every packet or flow ofcommunication sent or received by VMs 110 and/or VM capturing agents202. Moreover, any communication sent or received by hypervisor 108_(A), including data reported from hypervisor capturing agent 206, cancreate a network flow. Hypervisor capturing agent 206 can report suchflows in the form of a control flow to a remote device, such ascollectors 118 illustrated in FIG. 1. Hypervisor capturing agent 206 canreport each flow separately and/or in combination with other flows ordata.

When reporting a flow, hypervisor capturing agent 206 can include acapturing agent identifier that identifies hypervisor capturing agent206 as reporting the flow. Hypervisor capturing agent 206 can alsoinclude in the control flow a flow identifier, an IP address, atimestamp, metadata, a process ID, and any other information, asexplained below. In addition, capturing agents 206 can append theprocess and user information (i.e., which process and/or user isassociated with a particular flow) to the control flow. The additionalinformation as identified above can be applied to the control flow aslabels. Alternatively, the additional information can be included aspart of a header, a trailer, or a payload.

Hypervisor capturing agent 206 can also report multiple flows as a setof flows. When reporting a set of flows, hypervisor capturing agent 206can include a flow identifier for the set of flows and/or a flowidentifier for each flow in the set of flows. Hypervisor capturing agent206 can also include one or more timestamps and other information aspreviously explained, such as process and user information.

As previously explained, any communication captured or reported by VMcapturing agents 202 can flow through hypervisor 108 _(A). Thus,hypervisor capturing agent 206 can observe and capture any flows orpackets reported by VM capturing agents 202, including any controlflows. Accordingly, hypervisor capturing agent 206 can also report anypackets or flows reported by VM capturing agents 202 and any controlflows generated by VM capturing agents 202. For example, VM capturingagent 202 _(A) on VM 1 (110 _(A)) captures flow 1 (“F1”) and reports F1to collector 118 on FIG. 1. Hypervisor capturing agent 206 on hypervisor108 _(A) can also see and capture F1, as F1 would traverse hypervisor108 _(A) when being sent or received by VM 1 (110 _(A)). Accordingly,hypervisor capturing agent 206 on hypervisor 108 _(A) can also report F1to collector 118. Thus, collector 118 can receive a report of F1 from VMcapturing agent 202 _(A) on VM 1 (110 _(A)) and another report of F1from hypervisor capturing agent 206 on hypervisor 108 _(A).

When reporting F1, hypervisor capturing agent 206 can report F1 as amessage or report that is separate from the message or report of F1transmitted by VM capturing agent 202 _(A) on VM 1 (110 _(A)). However,hypervisor capturing agent 206 can also, or otherwise, report F1 as amessage or report that includes or appends the message or report of F1transmitted by VM capturing agent 202 _(A) on VM 1 (110 _(A)). In otherwords, hypervisor capturing agent 206 can report F1 as a separatemessage or report from VM capturing agent 202 _(A)'s message or reportof F1, and/or a same message or report that includes both a report of F1by hypervisor capturing agent 206 and the report of F1 by VM capturingagent 202 _(A) at VM 1 (110 _(A)). In this way, VM capturing agents 202at VMs 110 can report packets or flows received or sent by VMs 110, andhypervisor capturing agent 206 at hypervisor 108 _(A) can report packetsor flows received or sent by hypervisor 108 _(A), including any flows orpackets received or sent by VMs 110 and/or reported by VM capturingagents 202.

Hypervisor capturing agent 206 can run as a process, kernel module, orkernel driver on the host operating system associated with hypervisor108 _(A). Hypervisor capturing agent 206 can thus monitor any trafficsent and received by hypervisor 108 _(A), any processes associated withhypervisor 108 _(A), etc.

Server 106 _(A) can also have server capturing agent 208 running on it.Server capturing agent 208 can be a data inspection agent or sensordeployed on server 106 _(A) to capture data (e.g., packets, flows,traffic data, etc.) on server 106 _(A). Server capturing agent 208 canbe configured to export or report any data collected or captured byserver capturing agent 206 to a remote entity, such as collector 118,for example. Server capturing agent 208 can communicate or report suchdata using a network address of server 106 _(A), such as an IP addressof server 106 _(A).

Server capturing agent 208 can capture and report any packet or flow ofcommunication associated with server 106 _(A). For example, capturingagent 208 can report every packet or flow of communication sent orreceived by one or more communication interfaces of server 106 _(A).Moreover, any communication sent or received by server 106 _(A),including data reported from capturing agents 202 and 206, can create anetwork flow associated with server 106 _(A). Server capturing agent 208can report such flows in the form of a control flow to a remote device,such as collector 118 illustrated in FIG. 1. Server capturing agent 208can report each flow separately or in combination. When reporting aflow, server capturing agent 208 can include a capturing agentidentifier that identifies server capturing agent 208 as reporting theassociated flow. Server capturing agent 208 can also include in thecontrol flow a flow identifier, an IP address, a timestamp, metadata, aprocess ID, and any other information. In addition, capturing agent 208can append the process and user information (i.e., which process and/oruser is associated with a particular flow) to the control flow. Theadditional information as identified above can be applied to the controlflow as labels. Alternatively, the additional information can beincluded as part of a header, a trailer, or a payload.

Server capturing agent 208 can also report multiple flows as a set offlows. When reporting a set of flows, server capturing agent 208 caninclude a flow identifier for the set of flows and/or a flow identifierfor each flow in the set of flows. Server capturing agent 208 can alsoinclude one or more timestamps and other information as previouslyexplained.

Any communications captured or reported by capturing agents 202 and 206can flow through server 106 _(A). Thus, server capturing agent 208 canobserve or capture any flows or packets reported by capturing agents 202and 206. In other words, network data observed by capturing agents 202and 206 inside VMs 110 and hypervisor 108 _(A) can be a subset of thedata observed by server capturing agent 208 on server 106 _(A).Accordingly, server capturing agent 208 can report any packets or flowsreported by capturing agents 202 and 206 and any control flows generatedby capturing agents 202 and 206. For example, capturing agent 202 _(A)on VM 1 (110 _(A)) captures flow 1 (F1) and reports F1 to collector 118as illustrated on FIG. 1. Capturing agent 206 on hypervisor 108 _(A) canalso observe and capture F1, as F1 would traverse hypervisor 108 _(A)when being sent or received by VM 1 (110 _(A)). In addition, capturingagent 206 on server 106 _(A) can also see and capture F1, as F1 wouldtraverse server 106 _(A) when being sent or received by VM 1 (110 _(A))and hypervisor 108 _(A). Accordingly, capturing agent 208 can alsoreport F1 to collector 118. Thus, collector 118 can receive a report(i.e., control flow) regarding F1 from capturing agent 202 _(A) on VM 1(110 _(A)), capturing agent 206 on hypervisor 108 _(A), and capturingagent 208 on server 106 _(A).

When reporting F1, server capturing agent 208 can report F1 as a messageor report that is separate from any messages or reports of F1transmitted by capturing agent 202 _(A) on VM 1 (110 _(A)) or capturingagent 206 on hypervisor 108 _(A). However, server capturing agent 208can also, or otherwise, report F1 as a message or report that includesor appends the messages or reports or metadata of F1 transmitted bycapturing agent 202 _(A) on VM 1 (110 _(A)) and capturing agent 206 onhypervisor 108 _(A). In other words, server capturing agent 208 canreport F1 as a separate message or report from the messages or reportsof F1 from capturing agent 202 _(A) and capturing agent 206, and/or asame message or report that includes a report of F1 by capturing agent202 _(A), capturing agent 206, and capturing agent 208. In this way,capturing agents 202 at VMs 110 can report packets or flows received orsent by VMs 110, capturing agent 206 at hypervisor 108 _(A) can reportpackets or flows received or sent by hypervisor 108 _(A), including anyflows or packets received or sent by VMs 110 and reported by capturingagents 202, and capturing agent 208 at server 106 _(A) can reportpackets or flows received or sent by server 106 _(A), including anyflows or packets received or sent by VMs 110 and reported by capturingagents 202, and any flows or packets received or sent by hypervisor 108_(A) and reported by capturing agent 206.

Server capturing agent 208 can run as a process, kernel module, orkernel driver on the host operating system or a hardware component ofserver 106 _(A). Server capturing agent 208 can thus monitor any trafficsent and received by server 106 _(A), any processes associated withserver 106 _(A), etc.

In addition to network data, capturing agents 202, 206, and 208 cancapture additional information about the system or environment in whichthey reside. For example, capturing agents 202, 206, and 208 can capturedata or metadata of active or previously active processes of theirrespective system or environment, operating system user identifiers,metadata of files on their respective system or environment, timestamps,network addressing information, flow identifiers, capturing agentidentifiers, etc. Capturing agents 202, 206, and 208

Moreover, capturing agents 202, 206, 208 are not specific to anyoperating system environment, hypervisor environment, networkenvironment, or hardware environment. Thus, capturing agents 202, 206,and 208 can operate in any environment.

As previously explained, capturing agents 202, 206, and 208 can sendinformation about the network traffic they observe. This information canbe sent to one or more remote devices, such as one or more servers,collectors, engines, etc. Each capturing agent can be configured to sendrespective information using a network address, such as an IP address,and any other communication details, such as port number, to one or moredestination addresses or locations. Capturing agents 202, 206, and 208can send metadata about one or more flows, packets, communications,processes, events, etc.

Capturing agents 202, 206, and 208 can periodically report informationabout each flow or packet they observe. The information reported cancontain a list of flows or packets that were active during a period oftime (e.g., between the current time and the time at which the lastinformation was reported). The communication channel between thecapturing agent and the destination can create a flow in every interval.For example, the communication channel between capturing agent 208 andcollector 118 can create a control flow. Thus, the information reportedby a capturing agent can also contain information about this controlflow. For example, the information reported by capturing agent 208 tocollector 118 can include a list of flows or packets that were active athypervisor 108 _(A) during a period of time, as well as informationabout the communication channel between capturing agent 206 andcollector 118 used to report the information by capturing agent 206.

FIG. 2B illustrates a schematic diagram of example capturing agentdeployment 220 in an example network device. The network device isdescribed as leaf router 104 _(A), as illustrated in FIG. 1. However,this is for explanation purposes. The network device can be any othernetwork device, such as any other switch, router, etc.

In this example, leaf router 104 _(A) can include network resources 222,such as memory, storage, communication, processing, input, output, andother types of resources. Leaf router 104 _(A) can also includeoperating system environment 224. The operating system environment 224can include any operating system, such as a network operating system,embedded operating system, etc. Operating system environment 224 caninclude processes, functions, and applications for performingnetworking, routing, switching, forwarding, policy implementation,messaging, monitoring, and other types of operations.

Leaf router 104 _(A) can also include capturing agent 226. Capturingagent 226 can be an agent or sensor configured to capture network data,such as flows or packets, sent received, or processed by leaf router 104_(A). Capturing agent 226 can also be configured to capture otherinformation, such as processes, statistics, users, alerts, statusinformation, device information, etc. Moreover, capturing agent 226 canbe configured to report captured data to a remote device or network,such as collector 118 shown in FIG. 1, for example. Capturing agent 226can report information using one or more network addresses associatedwith leaf router 104 _(A) or collector 118. For example, capturing agent226 can be configured to report information using an IP assigned to anactive communications interface on leaf router 104 _(A).

Leaf router 104 _(A) can be configured to route traffic to and fromother devices or networks, such as server 106 _(A). Accordingly,capturing agent 226 can also report data reported by other capturingagents on other devices. For example, leaf router 104 _(A) can beconfigured to route traffic sent and received by server 106 _(A) toother devices. Thus, data reported from capturing agents deployed onserver 106 _(A), such as VM and hypervisor capturing agents on server106 _(A), would also be observed by capturing agent 226 and can thus bereported by capturing agent 226 as data observed at leaf router 104_(A). Such report can be a control flow generated by capturing agent226. Data reported by the VM and hypervisor capturing agents on server106 _(A) can therefore be a subset of the data reported by capturingagent 226.

Capturing agent 226 can run as a process or component (e.g., firmware,module, hardware device, etc.) in leaf router 104 _(A). Moreover,capturing agent 226 can be installed on leaf router 104 _(A) as asoftware or firmware agent. In some configurations, leaf router 104 _(A)itself can act as capturing agent 226. Moreover, capturing agent 226 canrun within operating system 224 and/or separate from operating system224.

FIG. 2C illustrates a schematic diagram of example reporting system 240in an example capturing agent topology. The capturing agent topologyincludes capturing agents along a path from a virtualized environment(e.g., VM and hypervisor) to the fabric 112.

Leaf router 104 _(A) can route packets or traffic 242 between fabric 112and server 106 _(A), hypervisor 108 _(A), and VM 110 _(A). Packets ortraffic 242 between VM 110 _(A) and leaf router 104 _(A) can flowthrough hypervisor 108 _(A) and server 106 _(A). Packets or traffic 242between hypervisor 108 _(A) and leaf router 104 _(A) can flow throughserver 106 _(A). Finally, packets or traffic 242 between server 106 _(A)and leaf router 104 _(A) can flow directly to leaf router 104 _(A).However, in some cases, packets or traffic 242 between server 106 _(A)and leaf router 104 _(A) can flow through one or more interveningdevices or networks, such as a switch or a firewall.

Moreover, VM capturing agent 202 _(A) at VM 110 _(A), hypervisorcapturing agent 206 _(A) at hypervisor 108 _(A), network devicecapturing agent 226 at leaf router 104 _(A), and any server capturingagent at server 106 _(A) (e.g., capturing agent running on hostenvironment of server 106 _(A)) can send reports 244 (also referred toas control flows) to collector 118 based on the packets or traffic 242captured at each respective capturing agent. Reports 244 from VMcapturing agent 202 _(A) to collector 118 can flow through VM 110 _(A),hypervisor 108 _(A), server 106 _(A), and leaf router 104 _(A). Reports244 from hypervisor capturing agent 206 _(A) to collector 118 can flowthrough hypervisor 108 _(A), server 106 _(A), and leaf router 104 _(A).Reports 244 from any other server capturing agent at server 106 _(A) tocollector 118 can flow through server 106 _(A) and leaf router 104 _(A).Finally, reports 244 from network device capturing agent 226 tocollector 118 can flow through leaf router 104 _(A). Although reports244 are depicted as being routed separately from traffic 242 in FIG. 2C,one of ordinary skill in the art will understand that reports 244 andtraffic 242 can be transmitted through the same communicationchannel(s).

Reports 244 can include any portion of packets or traffic 242 capturedat the respective capturing agents. Reports 244 can also include otherinformation, such as timestamps, process information, capturing agentidentifiers, flow identifiers, flow statistics, notifications, logs,user information, system information, etc. Some or all of thisinformation can be appended to reports 244 as one or more labels,metadata, or as part of the packet(s)' header, trailer, or payload. Forexample, if a user opens a browser on VM 110 _(A) and navigates toexamplewebsite.com, VM capturing agent 202 _(A) of VM 110 _(A) candetermine which user operating system user) of VM 110 _(A) (e.g.,username “johndoe85”) and which process being executed on the operatingsystem of VM 110 _(A) (e.g., “chrome.exe”) were responsible for theparticular network flow to and from examplewebsite.com. Once suchinformation is determined, the information can be included in report 244as labels for example, and report 244 can be transmitted from VMcapturing agent 202 _(A) to collector 118. Such additional informationcan help system 240 to gain insight into flow information at the processand user level, for instance. This information can be used for security,optimization, and determining structures and dependencies within system240.

In some examples, the reports 244 can include various statistics and/orusage information reported by the respective capturing agents. Forexample, the reports 244 can indicate an amount of traffic captured bythe respective capturing agent, which can include the amount of trafficsent, received, and generated by the capturing agent's host; a type oftraffic captured, such as video, audio, Web (e.g., HTTP or HTTPS),database queries, application traffic, etc.; a source and/or destinationof the traffic, such as a destination server or application, a sourcenetwork or device, a source or destination address or name (e.g., IPaddress, DNS name, FQDN, packet label, MAC address, LAN, VNID, VxLAN,source or destination domain, etc.); a source and/or destination port(e.g., port 25, port 80, port 443, port 8080, port 22); a trafficprotocol; traffic metadata; etc. The reports 244 can also includeindications of traffic or usage patterns and information, such asfrequency of communications, intervals, type of requests, type ofresponses, triggering processes or events (e.g., causality), resourceusage, etc.

Each of the capturing agents 202 _(A), 206 _(A), 226 can include arespective unique capturing agent identifier on each of reports 244 itsends to collector 118, to allow collector 118 to determine whichcapturing agent sent the report. Capturing agent identifiers in reports244 can also be used to determine which capturing agents reported whatflows. This information can then be used to determine capturing agentplacement and topology, as further described below, as well as mappingindividual flows to processes and users. Such additional insights gainedcan be useful for analyzing the data in reports 244, as well astroubleshooting, security, visualization, configuration, planning, andmanagement, and so forth.

As previously noted, the topology of the capturing agents can beascertained from the reports 244. To illustrate, a packet received by VM110 _(A) from fabric 112 can be captured and reported by VM capturingagent 202 _(A). Since the packet received by VM 110 _(A) will also flowthrough leaf router 104 _(A) and hypervisor 108 _(A), it can also becaptured and reported by hypervisor capturing agent 206 _(A) and networkdevice capturing agent 226. Thus, for a packet received by VM 110 _(A)from fabric 112, collector 118 can receive a report of the packet fromVM capturing agent 202 _(A), hypervisor capturing agent 206 _(A), andnetwork device capturing agent 226.

Similarly, a packet sent by VM 110 _(A) to fabric 112 can be capturedand reported by VM capturing agent 202 _(A). Since the packet sent by VM110 _(A) will also flow through leaf router 104 _(A) and hypervisor 108_(A), it can also be captured and reported by hypervisor capturing agent206 _(A) and network device capturing agent 226. Thus, for a packet sentby VM 110 _(A) to fabric 112, collector 118 can receive a report of thepacket from VM capturing agent 202 _(A), hypervisor capturing agent 206_(A), and network device capturing agent 226.

On the other hand, a packet originating at, or destined to, hypervisor108 _(A), can be captured and reported by hypervisor capturing agent 206_(A) and network device capturing agent 226, but not VM capturing agent202 _(A), as such packet may not flow through VM 110 _(A). Moreover, apacket originating at, or destined to, leaf router 104 _(A), will becaptured and reported by network device capturing agent 226, but not VMcapturing agent 202 _(A), hypervisor capturing agent 206 _(A), or anyother capturing agent on server 106 _(A), as such packet may not flowthrough VM 110 _(A), hypervisor 108 _(A), or server 106 _(A).

In another example, if the reports 244 indicate that the VM capturingagent 202 has been generating unexpected, improper, or excessivetraffic, such as sending packets or commands to a new or differentdevice other than collector 118—or other than any other system withwhich VM capturing agent 202 is expected or configured to communicatewith—or sending the wrong types of packets (e.g., other than reports244) or sending traffic at unexpected times or events (e.g., withoutbeing triggered by a predefined setting or event such as the capturingof a packet processed by the host), then one can assume that VMcapturing agent 202 has been compromised or is being manipulated by anunauthorized user or device.

Reports 244 can be transmitted to collector 118 periodically as newpackets or traffic 242 are captured by a capturing agent, or otherwisebased on a schedule, interval, or event, for example. Further, eachcapturing agent can send a single report or multiple reports tocollector 118. For example, each of the capturing agents can beconfigured to send a report to collector 118 for every flow, packet,message, communication, or network data received, transmitted, and/orgenerated by its respective host (e.g., VM 110 _(A), hypervisor 108_(A), server 106 _(A), and leaf router 104 _(A)). As such, collector 118can receive a report of a same packet from multiple capturing agents. Inother examples, one or more capturing agents can be configured to send areport to collector 118 for one or more flows, packets, messages,communications, network data, or subset(s) thereof, received,transmitted, and/or generated by the respective host during a period oftime or interval.

FIG. 3 illustrates a schematic diagram of an example configuration 300for collecting capturing agent reports (i.e., control flows). Inconfiguration 300, traffic between fabric 112 and VM 110 _(A) isconfigured to flow through hypervisor 108 _(A). Moreover, trafficbetween fabric 112 and hypervisor 108 _(A) is configured to flow throughleaf router 104 _(A).

VM capturing agent 202 _(A) can be configured to report to collector 118traffic sent, received, or processed by VM 110 _(A). Hypervisorcapturing agent 210 can be configured to report to collector 118 trafficsent, received, or processed by hypervisor 108 _(A). Finally, networkdevice capturing agent 226 can be configured to report to collector 118traffic sent, received, or processed by leaf router 104 _(A).

Collector 118 can thus receive flows 302 from VM capturing agent 202_(A), flows 304 from hypervisor capturing agent 206 _(A), and flows 306from network device capturing agent 226. Flows 302, 304, and 306 caninclude control flows. Flows 302 can include flows captured by VMcapturing agent 202 _(A) at VM 110 _(A).

Flows 304 can include flows captured by hypervisor capturing agent 206_(A) at hypervisor 108 _(A). Flows captured by hypervisor capturingagent 206 _(A) can also include flows 302 captured by VM capturing agent202 _(A), as traffic sent and received by VM 110 _(A) will be receivedand observed by hypervisor 108 _(A) and captured by hypervisor capturingagent 206 _(A).

Flows 306 can include flows captured by network device capturing agent226 at leaf router 104 _(A). Flows captured by network device capturingagent 226 can also include flows 302 captured by VM capturing agent 202_(A) and flows 304 captured by hypervisor capturing agent 206 _(A), astraffic sent and received by VM 110 _(A) and hypervisor 108 _(A) isrouted through leaf router 104 _(A) and can thus be captured by networkdevice capturing agent 226.

Collector 118 can collect flows 302, 304, and 306, and store thereported data. Collector 118 can also forward some or all of flows 302,304, and 306, and/or any respective portion thereof, to engine 120.Engine 120 can process the information, including any information aboutthe capturing agents (e.g., agent placement, agent environment, etc.)and/or the captured traffic (e.g., statistics), received from collector118 to identify patterns, conditions, network or device characteristics;log statistics or history details; aggregate and/or process the data;generate reports, timelines, alerts, graphical user interfaces; detecterrors, events, inconsistencies; troubleshoot networks or devices;configure networks or devices; deploy services or devices; reconfigureservices, applications, devices, or networks; etc.

Collector 118 and/or engine 120 can map individual flows that traverseVM 110 _(A), hypervisor 108 _(A), and/or leaf router 104 _(A) to thespecific capturing agents at VM 110 _(A), hypervisor 108 _(A), and/orleaf router 104 _(A). For example, collector 118 or engine 120 candetermine that a particular flow that originated from VM 110 _(A) anddestined for fabric 112 was sent by VM 110 _(A) and such flow wasreported by VM capturing agent 202. It may be determined that, the sameflow was received by a process named Z on hypervisor 108 _(A) andforwarded to a process named W on leaf router 104 _(A) and also reportedby hypervisor capturing agent 206.

While engine 120 is illustrated as a separate entity, otherconfigurations are also contemplated herein. For example, engine 120 canbe part of collector 118 and/or a separate entity. Indeed, engine 120can include one or more devices, applications, modules, databases,processing components, elements, etc. Moreover, collector 118 canrepresent one or more collectors. For example, in some configurations,collector 118 can include multiple collection systems or entities, whichcan reside in one or more networks.

Having disclosed some basic system components and concepts, thedisclosure now turns to the exemplary method embodiment shown in FIG. 4.For the sake of clarity, the method is described in terms of collector118 and capturing agents 116, as shown in FIG. 1, configured to practicethe various steps in the method. However, the example methods can bepracticed by any software or hardware components, devices, etc.heretofore disclosed. The steps outlined herein are exemplary and can beimplemented in any combination thereof in any order, includingcombinations that exclude, add, or modify certain steps.

The current disclosure implements sensors within VMs, hypervisors,servers, and hardware switches which capture data sent and received ateach of these points and reports the data to a collector which canaggregate and maintain the reported, sensed data. The collector cantransmit the collected data from each sensor to the pipeline (e.g.,particular engine), which can analyze the aggregated data and identifyprecise amounts of packet loss at each point. The pipeline can identifypacket loss at each point by comparing data or packets captured andreported by sensors at each point. This comparison can be performed perflow, per link, or on a host basis.

Moreover, the pipeline can perform the comparison for data capturedwithin a specific time window. For example, the pipeline can comparedata from each point within a 30 minute time window. The pipeline canthen identify packet loss at each point and determine if there is aproblem at a specific point within the link, path, or flow. For example,the pipeline can analyze an aggregate of data captured for a 30 minutewindow of communications from S1 to H1 to S2. Based on the aggregateddata, the pipeline can determine that S1 reported 100% of the packets,H1 reported 90% of the packets, and S2, reported 80% of the packets.Here, the pipeline can thus determine that there is a 10% packet loss ateach of H1 and S2.

The concepts disclosed herein allow a centralized system to collect andaggregate data captured from sensors at each point within acommunication path over a specific period of time and compare theinformation reported at each point to identify packet loss at eachpoint. This mechanism can be implemented in a live environment and canaccurately and efficiently ascertain packet loss at each point within anetwork.

FIG. 4 illustrates a method aspect of this disclosure. An exemplarymethod can be performed by a system or any computing device whetherphysical or virtual. The method includes capturing first data associatedwith a first packet flow originating from a host (or computing device)using a first capture agent deployed at the host to yield first flowdata (402), capturing second data associated with a second packet floworiginating from the host from a second capture agent deployed outsideof the host to yield second flow data (404), and comparing the firstflow data and the second flow data to yield a difference (406). When thedifference is above a threshold value, the method includes determiningthat the second packet flow was transmitted by a component (e.g.,sender) that bypassed one of an operating stack of the host and a packetcapture agent on the host, to yield a determination (408).

One example of positioning the first capture agent “inside” of a hostand the second capture agent “outside” of the host includes the firstcapture agent at a first host and the second capture agent at a secondhost. The first host and second host can be different devices or indifferent virtual layers or in the same layer. For example, the firsthost can be the virtual machine on a device and the second host can bethe hypervisor on the same device or a different device. Or the firsthost can be a switch and the second host can be a server, hypervisor, orvirtually machine. A host can also refer to an environment which can bethe actual device but it can also be the operating environment (e.g.,OS, hypervisor, VM, etc.).

The first data and the second data can include metadata associatedrespectively with the first packet flow and the second packet flow orfirst packet content of the first packet flow and second packet contentof the second packet flow. The data can also include network data oractivity. A collector can receive the first flow data and the secondflow data and perform the step of comparing the first flow data and thesecond flow data. When the difference is above a threshold value, thestep of determining that the second packet flow was transmitted by acomponent that bypassed one of the operating stack of the host and thepacket capture agent of the host further includes determining thathidden network traffic exists (410).

When the hidden network traffic exists, the method further includesperforming a correcting action including one or more of: isolating avirtual machine, isolating a container, limiting packets to and from thecomputing device/host, requiring all packets to and from the computingdevice/host to flow through an operating stack of the computingdevice/host, isolating the computing device/host, shutting down thecomputing device/host, and notifying an administrator (412). Othercorrecting actions are contemplated herein. Non-limiting examples ofcorrecting actions include, without limitation, blacklisting asource/sender, address, or flow; adjusting the granularity of datacaptured and/or reported by the capturing agents associated with thehidden traffic; adjusting one or more network or security rules orpolicies, such as a firewall rule, an access policy, a traffic orresource allocation policy, a policy defining the availability and/oruse of resources by elements associated with the hidden traffic and/orfor processing the hidden network traffic; flagging the hidden traffic;separating the hidden traffic from other traffic collected (e.g.,maintaining the hidden traffic at a separate location, log, and/orstorage), etc.

The method can also include identifying a computing environment thatgenerated the first packet flow and the second packet flow. Based on thedetermination, the method also can include determining that hiddennetwork traffic exists and/or thereafter taking a corrective action or alimiting action to reduce the negative effect of the threat. With theinformation identified from the collector, the system can also predict apresence of a malicious entity in the host based on the hidden networktraffic and/or other data.

The malicious entity of course can be in any host whether it is aphysical and/or software switch, a physical or virtual server, acomputing device, a hypervisor, a virtual machine, a container, anoperating system (e.g., host operating system, guest operating system,kernel, etc.), an ASIC (application specific integrated circuit), acontroller (e.g., BMC), a memory device, a virtual workload, and soforth. The malicious entity or hidden traffic generator can infect anyphysical, virtual/software device or host. Additional information aboutthe packet flows can be derived from one or more external, such asmalware trackers or lookup databases (e.g., whois, etc.), and/or dataobtained from the various layers of a network including a physicallayer, a hypervisor layer and a virtual layer. The packet flow data fromthe various capture agents can be based, at least in part, on captureagents configured in a device hardware layer 104 _(A), a hypervisorlayer 108 _(A), and/or a virtual machine layer 110 _(A). The dataobtained from these capture agents can also be coordinated with externaldata or other data to arrive at conclusions about the packet flow.

With the information at the various levels, increased fine tuning interms of identifying hidden processes can occur with respect toidentifying more specific details about the packet flow at variouslayers. For example, detecting traffic information between differentlayers such as at a hypervisor as well as one of its virtual machines,can provide data to identify a hidden process and particularly a processthat seeks to bypass an operating system layer in the entity which ishosting the course of the hidden process.

The hypervisors will each have a virtual or software switch and eachvirtual machine can also have a virtual network interface. With theconcepts disclosed herein, one can analyze the behavior of these virtualswitches and/or virtual network interfaces and use that data foridentifying hidden processes. Various inferences can be made based onbehavior detected at different layers and/or by different components(e.g., physical or virtual switches, virtual network interfaces, etc.).Information about the topology of the various hosts and/or capturingagents can be helpful when analyzing the reported data for determiningmalicious activity or hidden processes or traffic. For example, trafficcaptured by an agent residing at a virtual machine should also bereported by the capture agent residing at the hypervisor hosting thevirtual machine.

With knowledge about the topology, identity, settings, and type of hostsinvolved in a reported communication, specific inferences can be made ifthe captured and/or reported data indicates a pattern or deviation fromthe activity or behavior expected based on such knowledge. In otherexamples, knowledge about the corresponding forwarding models orpatterns for each of the different layers or switching elements (e.g.,software switch at a hypervisor, virtual network interface at virtualmachine, etc.) can be considered along with the reported data from thecapturing agents to infer malicious activity or abnormal behavior.

FIG. 5 illustrates a listing 500 of example fields on a capturing agentreport. The listing 500 can include one or more fields, such as:

Flow identifier (e.g., unique identifier associated with the flow).

Capturing agent identifier (e.g., data uniquely identifying reportingcapturing agent).

Timestamp (e.g., time of event, report, etc.).

Interval (e.g., time between current report and previous report,interval between flows or packets, interval between events, etc.).

Duration (e.g., duration of event, duration of communication, durationof flow, duration of report, etc.).

Flow direction (e.g., egress flow, ingress flow, etc.).

Application identifier (e.g., identifier of application associated withflow, process, event, or data).

Port (e.g., source port, destination port, layer 4 port, etc.).

Destination address (e.g., interface address associated withdestination. IP address, domain name, network address, hardware address,virtual address, physical address, etc.).

Source address (e.g., interface address associated with source, IPaddress, domain name, network address, hardware address, virtualaddress, physical address, etc.).

Interface (e.g., interface address, interface information, etc.).

Protocol (e.g., layer 4 protocol, layer 3 protocol, etc.).

Event (e.g., description of event, event identifier, etc.).

Flag (e.g., layer 3 flag, flag options, etc.).

Tag (e.g., virtual local area network tag, etc.)

Process (e.g., process identifier, etc.).

User (e.g., OS username, etc.).

Bytes (e.g., flow size, packet size, transmission size, etc.).

Sensor Type (e.g., the type of virtualized environment hosting thecapturing agent, such as hypervisor or VM; the type of virtual networkdevice, such as VNIC. LINUX bridge, OVS, software switch, etc.).

The listing 500 includes a non-limiting example of fields in a report.Other fields and data items are also contemplated herein, such ashandshake information, system information, network address associatedwith capturing agent or host, operating system environment information,network data or statistics, process statistics, system statistics, etc.The order in which these fields are illustrated is also exemplary andcan be rearranged in any other way. One or more of these fields can bepart of a header, a trailer, or a payload of in one or more packets.Moreover, one or more of these fields can be applied to the one or morepackets as labels. Each of the fields can include data, metadata, and/orany other information relevant to the fields.

The disclosure now turns to the example network device and systemillustrated in FIGS. 6 and 7A-B.

FIG. 6 illustrates an example network device 610 according to someembodiments. Network device 610 includes a master central processingunit (CPU) 662, interfaces 668, and a bus 615 (e.g., a PCI bus). Whenacting under the control of appropriate software or firmware, the CPU662 is responsible for executing packet management, error detection,and/or routing functions. The CPU 662 preferably accomplishes all thesefunctions under the control of software including an operating systemand any appropriate applications software. CPU 662 may include one ormore processors 663 such as a processor from the Motorola family ofmicroprocessors or the MIPS family of microprocessors. In an alternativeembodiment, processor 663 is specially designed hardware for controllingthe operations of router 610. In a specific embodiment, a memory 661(such as non-volatile RAM and/or ROM) also forms part of CPU 662.However, there are many different ways in which memory could be coupledto the system.

The interfaces 668 are typically provided as interface cards (sometimesreferred to as “line cards”). Generally, they control the sending andreceiving of data packets over the network and sometimes support otherperipherals used with the router 610. Among the interfaces that may beprovided are Ethernet interfaces, frame relay interfaces, cableinterfaces, DSL interfaces, token ring interfaces, and the like. Inaddition, various very high-speed interfaces may be provided such asfast token ring interfaces, wireless interfaces, Ethernet interfaces,Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POSinterfaces, FDDI interfaces and the like. Generally, these interfacesmay include ports appropriate for communication with the appropriatemedia. In some cases, they may also include an independent processorand, in some instances, volatile RAM. The independent processors maycontrol such communications intensive tasks as packet switching, mediacontrol and management. By providing separate processors for thecommunications intensive tasks, these interfaces allow the mastermicroprocessor 662 to efficiently perform muting computations networkdiagnostics, security functions, etc.

Although the system shown in FIG. 6 is one specific network device ofthe present disclosure, it is by no means the only network devicearchitecture on which the present disclosure can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc, is often used.Further, other types of interfaces and media could also be used with therouter.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 661) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc.

FIG. 7A and FIG. 7B illustrate example system embodiments. The moreappropriate embodiment will be apparent to those of ordinary skill inthe art when practicing the present technology. Persons of ordinaryskill in the art will also readily appreciate that other systemembodiments are possible.

FIG. 7A illustrates a conventional system bus computing systemarchitecture 700 wherein the components of the system are in electricalcommunication with each other using a bus 705. Exemplary system 700includes a processing unit (CPU or processor) 710 and a system bus 705that couples various system components including the system memory 715,such as read only memory (ROM) 720 and random access memory (RAM) 725,to the processor 710. The system 700 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 710. The system 700 can copy data from the memory715 and/or the storage device 730 to the cache 712 for quick access bythe processor 710. In this way, the cache can provide a performanceboost that avoids processor 710 delays while waiting for data. These andother modules can control or be configured to control the processor 710to perform various actions. Other system memory 715 may be available foruse as well. The memory 715 can include multiple different types ofmemory with different performance characteristics. The processor 710 caninclude any general purpose processor and a hardware module or softwaremodule, such as module 1 732, module 2 734, and module 3 736 stored instorage device 730, configured to control the processor 710 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. The processor 710 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction with the computing device 700, an inputdevice 745 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 735 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 700. The communications interface740 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 730 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMS) 725, read only memory (ROM) 720, andhybrids thereof.

The storage device 730 can include software modules 732, 734, 736 forcontrolling the processor 710. Other hardware or software modules arecontemplated. The storage device 730 can be connected to the system bus705. In one aspect, a hardware module that performs a particularfunction can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 710, bus 705, display 735, and soforth, to carry out the function.

FIG. 7B illustrates an example computer system 750 having a chipsetarchitecture that can be used in executing the described method andgenerating and displaying a graphical user interface (GUI). Computersystem 750 is an example of computer hardware, software, and firmwarethat can be used to implement the disclosed technology. System 750 caninclude a processor 755, representative of any number of physicallyand/or logically distinct resources capable of executing software,firmware, and hardware configured to perform identified computations.Processor 755 can communicate with a chipset 760 that can control inputto and output from processor 755. In this example, chipset 760 outputsinformation to output device 765, such as a display, and can read andwrite information to storage device 770 which can include magneticmedia, and solid state media, for example. Chipset 760 can also readdata from and write data to RAM 775. A bridge 780 for interfacing with avariety of user interface components 785 can be provided for interfacingwith chipset 760. Such user interface components 785 can include akeyboard, a microphone, touch detection and processing circuitry, apointing device, such as a mouse, and so on. In general, inputs tosystem 750 can come from any of a variety of sources, machine generatedand/or human generated.

Chipset 760 can also interface with one or more communication interfaces790 that can have different physical interfaces. Such communicationinterfaces can include interfaces for wired and wireless local areanetworks, for broadband wireless networks, as well as personal areanetworks. Some applications of the methods for generating, displaying,and using the GUI disclosed herein can include receiving ordereddatasets over the physical interface or be generated by the machineitself by processor 755 analyzing data stored in storage 770 or 775.Further, the machine can receive inputs from a user via user interfacecomponents 785 and execute appropriate functions, such as browsingfunctions by interpreting these inputs using processor 755.

It can be appreciated that example systems 700 and 750 can have morethan one processor 710 or be part of a group or cluster of computingdevices networked together to provide greater processing capability. Inone aspect, reference to a “processor” can mean a group of processors ofthe same or different types. For example, the “processor” can include acentral processing unit and a graphical processing unit. The “processor”can include one or multiple virtual and/or hardware processors.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks including devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can include,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can includehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims. Moreover, claimlanguage reciting “at least one of” a set indicates that one member ofthe set or multiple members of the set satisfy the claim.

It should be understood that features or configurations herein withreference to one embodiment or example can be implemented in, orcombined with, other embodiments or examples herein. That is, terms suchas “embodiment”, “variation”, “aspect”, “example”, “configuration”,“implementation”, “case”, and any other terms which may connote anembodiment, as used herein to describe specific features orconfigurations, are not intended to limit any of the associated featuresor configurations to a specific or separate embodiment or embodiments,and should not be interpreted to suggest that such features orconfigurations cannot be combined with features or configurationsdescribed with reference to other embodiments, variations, aspects,examples, configurations, implementations, cases, and so forth. In otherwords, features described herein with reference to a specific example(e.g., embodiment, variation, aspect, configuration, implementation,case, etc.) can be combined with features described with reference toanother example. Precisely, one of ordinary skill in the art willreadily recognize that the various embodiments or examples describedherein, and their associated features, can be combined with each other.

A phrase such as an “aspect” does not imply that such aspect isessential to the subject technology or that such aspect applies to allconfigurations of the subject technology. A disclosure relating to anaspect may apply to all configurations, or one or more configurations. Aphrase such as an aspect may refer to one or more aspects and viceversa. A phrase such as a “configuration” does not imply that suchconfiguration is essential to the subject technology or that suchconfiguration applies to all configurations of the subject technology. Adisclosure relating to a configuration may apply to all configurations,or one or more configurations. A phrase such as a configuration mayrefer to one or more configurations and vice versa. The word “exemplary”is used herein to mean “serving as an example or illustration.” Anyaspect or design described herein as “exemplary” is not necessarily tobe construed as preferred or advantageous over other aspects or designs.

Moreover, claim language reciting “at least one of” a set indicates thatone member of the set or multiple members of the set satisfy the claim.For example, claim language reciting “at least one of A, B, and C” or“at least one of A, B, or C” means A alone, B alone, C alone, A and Btogether, A and C together, B and C together, or A, B and C together.

What is claimed is:
 1. A method comprising: capturing first dataassociated with a first packet flow originating from a first host usinga first capture agent deployed at the first host to yield first flowdata; capturing second data associated with a second packet floworiginating from the first host using a second capture agent deployed ata second host to yield second flow data, wherein the first capturingagent is deployed in a first layer of a network and the second capturingagent is deployed in a second layer of the network; comparing the firstflow data and the second flow data to yield a difference; and when thedifference is above a threshold value, determining that the secondpacket flow was transmitted by a component that bypassed an operatingstack of the first host or a packet capture agent on the first host, toyield a determination that hidden network traffic exists, and performinga correcting action comprising one or more of: isolating a virtualmachine, isolating a container, limiting packets to and from the firsthost, requiring all packets to and from the first host to flow throughthe operating stack of the first host, isolating the first host,shutting down the first host, or notifying an administrator.
 2. Themethod of claim 1, wherein the first data and the second data comprisemetadata associated respectively with the first packet flow and thesecond packet flow.
 3. The method of claim 1, wherein the first datacomprises first packet content of the first packet flow and the seconddata comprise second packet content of the second packet flow.
 4. Themethod of claim 1, wherein the first data and the second data comprisenetwork data.
 5. The method of claim 1, wherein a collector receives thefirst flow data and the second flow data and performs the step ofcomparing the first flow data and the second flow data.
 6. The method ofclaim 1, wherein the corrective action includes requiring all packets toand from first host to flow through the operating stack of hte firsthost.
 7. The method of claim 6, wherein the correcting action includesisolating the virtual machine and/or the container.
 8. The method ofclaim 1, further comprising: identifying a computing environment thatgenerated the first packet flow and the second packet flow.
 9. Themethod of claim 1, further comprising: determining that hidden networktraffic exists based on the determination.
 10. The method of claim 9,wherein the corrective action includes isolating or shutting down thefirst host.
 11. The method of claim 9, further comprising: predicting apresence of a malicious entity in the first host based on the hiddennetwork traffic.
 12. A system comprising: a processor; and acomputer-readable storage medium storing instructions which, whenexecuted by the processor, cause the processor to perform operationscomprising: capturing first data associated with a first packet floworiginating from a first host using a first capture agent deployed atthe first host to yield first flow data; capturing second dataassociated with a second packet flow originating from the first hostusing a second capture agent deployed at a second host to yield secondflow data, wherein the first capturing agent is deployed in a firstlayer of a network and the second capturing agent is deployed in asecond layer of the network; comparing the first flow data and thesecond flow data to yield a difference; and when the difference is abovea threshold value, determining that the second packet flow wastransmitted by a component that bypassed one of an operating stack ofthe first host and a packet capture agent on the first host, to yield adetermination that hidden network traffic exists, and performing acorrecting action comprising one or more of: isolating a virtualmachine, isolating a container, limiting packets to and from the firsthost, requiring all packets to and from the first host to flow throughthe operating stack of the first host, isolating the first host,shutting down the first host, or notifying an administrator.
 13. Thesystem of claim 12, wherein the first data and the second data compriseone of (1) metadata associated respectively with the first packet flowand the second packet flow or (2) network data.
 14. The system of claim12, wherein the first data comprises first packet content of the firstpacket flow and the second data comprise second packet content of thesecond packet flow.
 15. The system of claim 12, wherein a collectorreceives the first flow data and the second flow data and performs thestep of comparing the first flow data and the second flow data.
 16. Thesystem of claim 12, wherein the corrective action includes requiring allpackets to and from the first host to flow through the operating stackof the first host.
 17. The system of claim 16, wherein the correctingaction includes isolating the virtual machine and/or the container. 18.The system of claim 12, wherein the computer-readable storage mediumstores additional instructions which, when executed by the processor,cause the processor to perform further operations comprising:identifying a computing environment that generated the first packet flowand the second packet flow.
 19. The system of claim 12, wherein thecomputer-readable storage medium stores additional instructions which,when executed by the processor, cause the processor to perform furtheroperations comprising: based on the determination, determining thathidden network traffic exists.
 20. The system of claim 19, furthercomprising: predicting a presence of a malicious entity in the firsthost based on the hidden network traffic.